Abstract
Smart parking is one of the most interesting applications of vehicular ad hoc networks, since drivers looking for free parking slots seriously impact traffic conditions and road congestion. The pandemic experience affecting the world with COVID-19 virus since 2020 has radically changed the citizens lives and their habits. Any sector, from sanitary to economics, had to adapt itself to a new approach to everyday-life. Mobility is included in such a change and researchers in this field should contribute in this direction. In this work, we propose an innovative smart technique for parking detection, which takes care of anti-covid standards: indeed, such a parking schema maps vehicles in the available slots with the aim of reducing assembly, after the vehicle has been parked. After analyzing the parking process, we conclude that the arrival to the parking area, and the moment when one leaves that area can be source of crowd. In order to reduce this phenomenon, we perform a user profiling with the aim of reducing the probability that drivers are in the same place at the same time. We achieve the goal by computing a risk factor for any pair of vehicles populating the car parking.
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Balzano, W., Stranieri, S. (2021). COVID-Prevention-Based Parking with Risk Factor Computation. In: Barolli, L., Yim, K., Enokido, T. (eds) Complex, Intelligent and Software Intensive Systems. CISIS 2021. Lecture Notes in Networks and Systems, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-030-79725-6_12
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DOI: https://doi.org/10.1007/978-3-030-79725-6_12
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